Total 50,676 skills, AI & Machine Learning has 8495 skills
Showing 12 of 8495 skills
Generate LLM skills from documentation, codebases, and GitHub repositories
Convert natural language queries to SQL. Use for database queries, data analysis, and reporting.
Create production-ready skills from expert knowledge. Extracts domain expertise and system ontologies, uses scripts for deterministic work, loads knowledge progressively. Use when building skills that must work reliably in production.
Create AI tools for use with Vercel AI SDK agents. Use when asked to "create AI tools", "add agent tools", "create tool for AI", or "add tools to agent".
Meta-prompting skill that creates well-structured, verifiable, low-hallucination prompts for any use case. Use when the user wants to create, refine, or improve a prompt — including system prompts, role prompts, task prompts, or any AI instruction set. Triggers on requests like "create a prompt for...", "help me write a prompt", "refine this prompt", "make a better prompt for...", or "generate a prompt that...".
Multi-agent coordination expert for agent-swarm MCP. Use when the user asks about swarm coordination, delegating tasks to agents, checking swarm status, agent messaging, or managing multi-agent workflows.
Use when building persistent codebase intelligence for AI agents or integrating knowledge systems via MCP
Understand ContextVM core concepts, architecture decisions, and frequently asked questions. Use when users need clarification on what ContextVM is, why it uses Nostr, decentralization benefits, public vs private servers, network topology, or comparisons with traditional MCP.
Autonomous multi-agent task orchestration with dependency analysis, parallel tmux/Codex execution, and self-healing heartbeat monitoring. Use for large projects with multiple issues/tasks that need coordinated parallel execution.
Multi-Agent Architecture Design and Intelligent Spawn System. Use this skill when you need to design a multi-agent system, configure specialized agents, implement intelligent task distribution, or optimize concurrent processing capabilities.
Digital archiving workflows with AI enrichment, entity extraction, and knowledge graph construction. Use when building content archives, implementing AI-powered categorization, extracting entities and relationships, or integrating multiple data sources. Covers patterns from the Jay Rosen Digital Archive project.
Image processing, object detection, segmentation, and vision models. Use for image classification, object detection, or visual analysis tasks.